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The growing impact of preprint servers enables the rapid sharing oftime-sensitive research. Likewise, it is becoming increasingly difficult todistinguish high-quality, peer-reviewed research from preprints. Althoughpreprints are often later published in peer-reviewed journals, this informationis often missing from preprint servers. To overcome this problem, thePreprintResolver was developed, which uses four literature databases (DBLP,SemanticScholar, OpenAlex, and CrossRef / CrossCite) to identifypreprint-publication pairs for the arXiv preprint server. The target audiencefocuses on, but is not limited to inexperienced researchers and students,especially from the field of computer science. The tool is based on a fuzzymatching of author surnames, titles, and DOIs. Experiments were performed on asample of 1,000 arXiv-preprints from the research field of computer science andwithout any publication information. With 77.94 %, computer science is highlyaffected by missing publication information in arXiv. The results show that thePreprintResolver was able to resolve 603 out of 1,000 (60.3 %) arXiv-preprintsfrom the research field of computer science and without any publicationinformation. All four literature databases contributed to the final result. Ina manual validation, a random sample of 100 resolved preprints was checked. Forall preprints, at least one result is plausible. For nine preprints, more thanone result was identified, three of which are partially invalid. In conclusionthe PreprintResolver is suitable for individual, manually reviewed requests,but less suitable for bulk requests. The PreprintResolver tool(https://preprintresolver.eu, Available from 2023-08-01) and source code(https://gitlab.com/ippolis_wp3/preprint-resolver, Accessed: 2023-07-19) isavailable online.

PreprintResolver: Improving Citation Quality by Resolving Published Versions of ArXiv Preprints using Literature Databases